Abstract
Recently, Güssregen et al. used solute–solvent distribution functions calculated by the 3D Reference Interaction Site Model (3DRISM) in a 3D-QSAR model to predict the binding affinities of serine protease inhibitors; this approach was referred to as Comparative Analysis of 3D RISM MAps (CARMa). [J. Chem. Inf. Model., 2017, 57, 1652-1666] Here we extend this idea by introducing probe atoms into the 3DRISM solvent model in order to directly capture other molecular interactions in addition to those related to hydration/dehydration. Benchmark results for six different protein- ligand systems show that CARMa models trained on probe atom descriptors gives consistently more accurate predictions than CoMFA, and other common QSAR approaches.
Original language | English |
---|---|
Number of pages | 40 |
Journal | Journal of Chemical Information and Modeling |
Early online date | 15 Mar 2018 |
DOIs | |
Publication status | E-pub ahead of print - 15 Mar 2018 |
Keywords
- genetic algorithm
- partial least squares
- binding affinity
- molecular modelling